Add affinity propagation

.github/workflows/ci.yml

@@ -17,7 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.6'
+          - '1.10'
           - '1'
         os:
           - ubuntu-latest

Project.toml

@@ -49,7 +49,7 @@ StatisticalTraits = "3"
 Statistics = "<0.0.1, 1"
 StatsBase = "0.32,0.33, 0.34"
 Tables = "0.2,1.0"
-julia = "1.6"
+julia = "1.10"
 
 [extras]
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"

src/MLJModels.jl

@@ -72,6 +72,7 @@ include("metadata.jl")
 
 # read in the metadata:
 metadata_file = joinpath(srcdir, "registry", "Metadata.toml")
+Base.include_dependency(metadata_file)
 const INFO_GIVEN_HANDLE = info_given_handle(metadata_file)
 const PKGS_GIVEN_NAME = pkgs_given_name(INFO_GIVEN_HANDLE)
 const AMBIGUOUS_NAMES = ambiguous_names(INFO_GIVEN_HANDLE)

src/registry/Metadata.toml

@@ -5939,6 +5939,42 @@
 ":reporting_operations" = "`()`"
 ":constructor" = "`RecursiveFeatureElimination`"
 
+[Clustering.AffinityPropagation]
+":input_scitype" = "`ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}`"
+":output_scitype" = "`ScientificTypesBase.Unknown`"
+":target_scitype" = "`ScientificTypesBase.Unknown`"
+":fit_data_scitype" = "`Tuple{}`"
+":predict_scitype" = "`ScientificTypesBase.Unknown`"
+":transform_scitype" = "`ScientificTypesBase.Unknown`"
+":inverse_transform_scitype" = "`ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}`"
+":target_in_fit" = "`false`"
+":is_pure_julia" = "`true`"
+":package_name" = "Clustering"
+":package_license" = "MIT"
+":load_path" = "MLJClusteringInterface.AffinityPropagation"
+":package_uuid" = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
+":package_url" = "https://github.com/JuliaStats/Clustering.jl"
+":is_wrapper" = "`false`"
+":supports_weights" = "`false`"
+":supports_class_weights" = "`false`"
+":supports_online" = "`false`"
+":docstring" = "To be added"
+":name" = "AffinityPropagation"
+":human_name" = "affinity propagation clusterer"
+":is_supervised" = "`false`"
+":prediction_type" = ":unknown"
+":abstract_type" = "`MLJModelInterface.Static`"
+":implemented_methods" = [":clean!", ":predict"]
+":hyperparameters" = "`(:damp, :maxiter, :tol, :preference, :metric)`"
+":hyperparameter_types" = "`(\"Float64\", \"Int64\", \"Float64\", \"Union{Nothing, Float64}\", \"Distances.SemiMetric\")`"
+":hyperparameter_ranges" = "`(nothing, nothing, nothing, nothing, nothing)`"
+":iteration_parameter" = "`nothing`"
+":supports_training_losses" = "`false`"
+":reports_feature_importances" = "`false`"
+":deep_properties" = "`()`"
+":reporting_operations" = "`(:predict,)`"
+":constructor" = "`nothing`"
+
 [Clustering.HierarchicalClustering]
 ":input_scitype" = "`Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}}`"
 ":output_scitype" = "`ScientificTypesBase.Unknown`"

src/registry/Models.toml

@@ -17,7 +17,7 @@ MLJBalancing = ["BalancedBaggingClassifier", "BalancedModel"]
 Imbalance = ["RandomOversampler", "SMOTENC", "TomekUndersampler", "ClusterUndersampler", "SMOTE", "SMOTEN", "ROSE", "RandomUndersampler", "ENNUndersampler", "BorderlineSMOTE1", "RandomWalkOversampler"]
 MLJTuning = ["TunedModel"]
 FeatureSelection = ["FeatureSelector", "RecursiveFeatureElimination"]
-Clustering = ["HierarchicalClustering", "DBSCAN", "KMeans", "KMedoids"]
+Clustering = ["HierarchicalClustering", "DBSCAN", "KMeans", "KMedoids", "AffinityPropagation"]
 EvoLinear = ["EvoSplineRegressor", "EvoLinearRegressor"]
 MLJText = ["TfidfTransformer", "CountTransformer", "BM25Transformer"]
 LightGBM = ["LGBMClassifier", "LGBMRegressor"]

test/runtests.jl

@@ -1,7 +1,12 @@
-# The next two lines added as a workaround to
-# https://github.com/JuliaLang/Pkg.jl/issues/3628 (Julia 1.6):
 import Pkg
-Pkg.add(name="Statistics", version=VERSION)
+
+if Base.VERSION >= v"1.10-"
+    # The issue with stdlib versions being fixed to 0.0.0 has been fixed in new versions of Julia
+else
+    # The next line added as a workaround to
+    # https://github.com/JuliaLang/Pkg.jl/issues/3628 (Julia 1.6):
+    Pkg.add(name="Statistics", version=VERSION, uuid="10745b16-79ce-11e8-11f9-7d13ad32a3b2")
+end
 
 using Test, MLJModels